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Bao T, Damtie MM, Wang CY, Li CL, Chen Z, Cho K, Wei W, Yuan P, Frost RL, Ni BJ. Iron-containing nanominerals for sustainable phosphate management: A comprehensive review and future perspectives. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:172025. [PMID: 38554954 DOI: 10.1016/j.scitotenv.2024.172025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/25/2024] [Accepted: 03/25/2024] [Indexed: 04/02/2024]
Abstract
Adsorption, which is a quick and effective method for phosphate management, can effectively address the crisis of phosphorus mineral resources and control eutrophication. Phosphate management systems typically use iron-containing nanominerals (ICNs) with large surface areas and high activity, as well as modified ICNs (mICNs). This paper comprehensively reviews phosphate management by ICNs and mICNs in different water environments. mICNs have a higher affinity for phosphates than ICNs. Phosphate adsorption on ICNs and mICNs occurs through mechanisms such as surface complexation, surface precipitation, electrostatic ligand exchange, and electrostatic attraction. Ionic strength influences phosphate adsorption by changing the surface potential and isoelectric point of ICNs and mICNs. Anions exhibit inhibitory effects on ICNs and mICNs in phosphate adsorption, while cations display a promoting effect. More importantly, high concentrations and molecular weights of natural organic matter can inhibit phosphate adsorption by ICNs and mICNs. Sodium hydroxide has high regeneration capability for ICNs and mICNs. Compared to ICNs with high crystallinity, those with low crystallinity are less likely to desorb. ICNs and mICNs can effectively manage municipal wastewater, eutrophic seawater, and eutrophic lakes. Adsorption of ICNs and mICNs saturated with phosphate can be used as fertilizers in agricultural production. Notably, mICNs and ICNs have positive and negative effects on microorganisms and aquatic organisms in soil. Finally, this study introduces the following: trends and prospects of machine learning-guided mICN design, novel methods for modified ICNs, mICN regeneration, development of mICNs with high adsorption capacity and selectivity for phosphate, investigation of competing ions in different water environments by mICNs, and trends and prospects of in-depth research on the adsorption mechanism of phosphate by weakly crystalline ferrihydrite. This comprehensive review can provide novel insights into the research on high-performance mICNs for phosphate management in the future.
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Huang Z, Song E, Chen Z, Yu P, Chen W, Lin H. Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression. BMC Med Genomics 2024; 17:133. [PMID: 38760670 PMCID: PMC11100188 DOI: 10.1186/s12920-024-01885-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 04/19/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND Parkinson's disease (PD) is a progressive neurodegenerative disease with increasing prevalence. Effective diagnostic markers and therapeutic methods are still lacking. Exploring key molecular markers and mechanisms for PD can help with early diagnosis and treatment improvement. METHODS Three datasets GSE174052, GSE77668, and GSE168496 were obtained from the GEO database to search differentially expressed circRNA (DECs), miRNAs (DEMis), and mRNAs (DEMs). GO and KEGG enrichment analyses, and protein-protein interaction (PPI) network construction were implemented to explore possible actions of DEMs. Hub genes were selected to establish circRNA-related competing endogenous RNA (ceRNA) networks. RESULTS There were 1005 downregulated DECs, 21 upregulated and 21 downregulated DEMis, and 266 upregulated and 234 downregulated DEMs identified. The DEMs were significantly enriched in various PD-associated functions and pathways such as extracellular matrix organization, dopamine synthesis, PI3K-Akt, and calcium signaling pathways. Twenty-one hub genes were screened out, and a PD-related ceRNA regulatory network was constructed containing 31 circRNAs, one miRNA (miR-371a-3p), and one hub gene (KCNJ6). CONCLUSION We identified PD-related molecular markers and ceRNA regulatory networks, providing new directions for PD diagnosis and treatment.
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Lin S, Chen Z, Li S, Chen B, Wu Y, Zheng Y, Huang J, Chen Y, Lin X, Yao H. Corrigendum to "Anti-tumor effect and mechanism of the total biflavonoid extract from S doederleinii on human cervical cancer cells in vitro and in vivo" [Heliyon 10(2) January 2024 e24778]. Heliyon 2024; 10:e30202. [PMID: 38807607 PMCID: PMC11130459 DOI: 10.1016/j.heliyon.2024.e30202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 04/22/2024] [Indexed: 05/30/2024] Open
Abstract
[This corrects the article DOI: 10.1016/j.heliyon.2024.e24778.].
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Dodonova A, Eich N, Eliseev D, Engelke F, Erdmann M, Fackeldey P, Fischer B, Hebbeker T, Hoepfner K, Ivone F, Jung A, Lee MY, Mastrolorenzo L, Merschmeyer M, Meyer A, Mukherjee S, Noll D, Novak A, Nowotny F, Pozdnyakov A, Rath Y, Redjeb W, Rehm F, Reithler H, Sarkisovi V, Schmidt A, Schuler SC, Sharma A, Stein A, Torres Da Silva De Araujo F, Vigilante L, Wiedenbeck S, Zaleski S, Dziwok C, Flügge G, Haj Ahmad W, Kress T, Nowack A, Pooth O, Stahl A, Ziemons T, Zotz A, Aarup Petersen H, Aldaya Martin M, Alimena J, Amoroso S, An Y, Baxter S, Bayatmakou M, Becerril Gonzalez H, Behnke O, Belvedere A, Bhattacharya S, Blekman F, Borras K, Brunner D, Campbell A, Cardini A, Cheng C, Colombina F, Consuegra Rodríguez S, Correia Silva G, De Silva M, Eckerlin G, Eckstein D, Estevez Banos LI, Filatov O, Gallo E, Geiser A, Giraldi A, Greau G, Guglielmi V, Guthoff M, Hinzmann A, Jafari A, Jeppe L, Jomhari NZ, Kaech B, Kasemann M, Kaveh H, Kleinwort C, Kogler R, Komm M, Krücker D, Lange W, Leyva Pernia D, Lipka K, Lohmann W, Mankel R, Melzer-Pellmann IA, Mendizabal Morentin M, Metwally J, Meyer AB, Milella G, Mussgiller A, Nürnberg A, Otarid Y, Pérez Adán D, Ranken E, Raspereza A, Ribeiro Lopes B, Rübenach J, Saggio A, Scham M, Schnake S, Schütze P, Schwanenberger C, Selivanova D, Shchedrolosiev M, Sosa Ricardo RE, Sreelatha Pramod LP, Stafford D, Vazzoler F, Ventura Barroso A, Walsh R, Wang Q, Wen Y, Wichmann K, Wiens L, Wissing C, Wuchterl S, Yang Y, Zimermmane Castro Santos A, Albrecht A, Albrecht S, Antonello M, Bein S, Benato L, Bonanomi M, Connor P, Eich M, El Morabit K, Fischer Y, Fröhlich A, Garbers C, Garutti E, Grohsjean A, Hajheidari M, Haller J, Jabusch HR, Kasieczka G, Keicher P, Klanner R, Korcari W, Kramer T, Kutzner V, Labe F, Lange J, Lobanov A, Matthies C, Mehta A, Moureaux L, Mrowietz M, Nigamova A, Nissan Y, Paasch A, Pena Rodriguez KJ, Quadfasel T, Raciti B, Rieger M, Savoiu D, Schindler J, Schleper P, Schröder M, Schwandt J, Sommerhalder M, Stadie H, Steinbrück G, Tews A, Wolf M, Brommer S, Burkart M, Butz E, Chwalek T, Dierlamm A, Droll A, Faltermann N, Giffels M, Gottmann A, Hartmann F, Hofsaess R, Horzela M, Husemann U, Klute M, Koppenhöfer R, Link M, Lintuluoto A, Maier S, Mitra S, Mormile M, Müller T, Neukum M, Oh M, Quast G, Rabbertz K, Regnery B, Shadskiy N, Shvetsov I, Simonis HJ, Trevisani N, Ulrich R, van der Linden J, Von Cube RF, Wassmer M, Wieland S, Wittig F, Wolf R, Wunsch S, Zuo X, Anagnostou G, Assiouras P, Daskalakis G, Kyriakis A, Papadopoulos A, Stakia A, Kontaxakis P, Melachroinos G, Panagiotou A, Papavergou I, Paraskevas I, Saoulidou N, Theofilatos K, Tziaferi E, Vellidis K, Zisopoulos I, Bakas G, Chatzistavrou T, Karapostoli G, Kousouris K, Papakrivopoulos I, Siamarkou E, Tsipolitis G, Zacharopoulou A, Adamidis K, Bestintzanos I, Evangelou I, Foudas C, Gianneios P, Kamtsikis C, Katsoulis P, Kokkas P, Kosmoglou Kioseoglou PG, Manthos N, Papadopoulos I, Strologas J, Bartók M, Hajdu C, Horvath D, Sikler F, Veszpremi V, Csanád M, Farkas K, Gadallah MMA, Kadlecsik Á, Major P, Mandal K, Pásztor G, Rádl AJ, Veres GI, Raics P, Ujvari B, Zilizi G, Bencze G, Czellar S, Karancsi J, Molnar J, Szillasi Z, Csorgo T, Nemes F, Novak T, Babbar J, Bansal S, Beri SB, Bhatnagar V, Chaudhary G, Chauhan S, Dhingra N, Gupta R, Kaur A, Kaur A, Kaur H, Kaur M, Kumar S, Meena M, Sandeep K, Sheokand T, Singh JB, Singla A, Ahmed A, Bhardwaj A, Chhetri A, Choudhary BC, Kumar A, Naimuddin M, Ranjan K, Saumya S, Acharya S, Baradia S, Barman S, Bhattacharya S, Bhowmik D, Dutta S, Dutta S, Gomber B, Palit P, Saha G, Sahu B, Sarkar S, Ameen MM, Behera PK, Behera SC, Chatterjee S, Jana P, Kalbhor P, Komaragiri JR, Kumar D, Panwar L, Pradhan R, Pujahari PR, Saha NR, Sharma A, Sikdar AK, Verma S, Aziz T, Das I, Dugad S, Kumar M, Mohanty GB, Suryadevara P, Bala A, Banerjee S, Chatterjee RM, Guchait M, Jain S, Karmakar S, Kumar S, Majumder G, Mazumdar K, Mukherjee S, Thachayath A, Bahinipati S, Das AK, Kar C, Maity D, Mal P, Mishra T, 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K, Silva P, Sphicas P, Stahl Leiton AG, Steen A, Summers S, Treille D, Tropea P, Tsirou A, Walter D, Wanczyk J, Wozniak KA, Zehetner P, Zejdl P, Zeuner WD, Bevilacqua T, Caminada L, Ebrahimi A, Erdmann W, Horisberger R, Ingram Q, Kaestli HC, Kotlinski D, Lange C, Missiroli M, Noehte L, Rohe T, Aarrestad TK, Androsov K, Backhaus M, Calandri A, Cazzaniga C, Datta K, De Cosa A, Dissertori G, Dittmar M, Donegà M, Eble F, Galli M, Gedia K, Glessgen F, Grab C, Hits D, Lustermann W, Lyon AM, Manzoni RA, Marchegiani M, Marchese L, Martin Perez C, Mascellani A, Nessi-Tedaldi F, Pauss F, Perovic V, Pigazzini S, Ratti MG, Reichmann M, Reissel C, Reitenspiess T, Ristic B, Riti F, Ruini D, Sanz Becerra DA, Seidita R, Steggemann J, Valsecchi D, Wallny R, Amsler C, Bärtschi P, Botta C, Brzhechko D, Canelli MF, Cormier K, Del Burgo R, Heikkilä JK, Huwiler M, Jin W, Jofrehei A, Kilminster B, Leontsinis S, Liechti SP, Macchiolo A, Meiring P, Mikuni VM, Molinatti U, Neutelings I, Reimers A, Robmann P, 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SS, Smith VJ, Stylianou N, Walkingshaw Pass K, White R, Ball AH, Bell KW, Belyaev A, Brew C, Brown RM, Cockerill DJA, Cooke C, Ellis KV, Harder K, Harper S, Holmberg ML, Linacre J, Manolopoulos K, Newbold DM, Olaiya E, Petyt D, Reis T, Salvi G, Schuh T, Shepherd-Themistocleous CH, Tomalin IR, Williams T, Bainbridge R, Bloch P, Brown CE, Buchmuller O, Cacchio V, Carrillo Montoya CA, Chahal GS, Colling D, Dancu JS, Dauncey P, Davies G, Davies J, Della Negra M, Fayer S, Fedi G, Hall G, Hassanshahi MH, Howard A, Iles G, Knight M, Langford J, Lyons L, Magnan AM, Malik S, Martelli A, Mieskolainen M, Nash J, Pesaresi M, Radburn-Smith BC, Richards A, Rose A, Seez C, Shukla R, Tapper A, Uchida K, Uttley GP, Vage LH, Virdee T, Vojinovic M, Wardle N, Winterbottom D, Coldham K, Cole JE, Khan A, Kyberd P, Reid ID, Abdullin S, Brinkerhoff A, Caraway B, Dittmann J, Hatakeyama K, Hiltbrand J, Kanuganti AR, McMaster B, Saunders M, Sawant S, Sutantawibul C, Toms M, Wilson J, Bartek R, Dominguez A, Huerta Escamilla C, Simsek AE, Uniyal R, Vargas Hernandez AM, Chudasama R, Cooper SI, Gleyzer SV, Perez CU, Rumerio P, Usai E, West C, Yi R, Akpinar A, Albert A, Arcaro D, Cosby C, Demiragli Z, Erice C, Fontanesi E, Gastler D, Jeon S, Rohlf J, Salyer K, Sperka D, Spitzbart D, Suarez I, Tsatsos A, Yuan S, Benelli G, Coubez X, Cutts D, Hadley M, Heintz U, Hogan JM, Kwon T, Landsberg G, Lau KT, Li D, Luo J, Mondal S, Narain M, Pervan N, Sagir S, Simpson F, Stamenkovic M, Wong WY, Yan X, Zhang W, Abbott S, Bonilla J, Brainerd C, Breedon R, Calderon De La Barca Sanchez M, Chertok M, Citron M, Conway J, Cox PT, Erbacher R, Jensen F, Kukral O, Mocellin G, Mulhearn M, Pellett D, Wei W, Yao Y, Zhang F, Bachtis M, Cousins R, Datta A, Hauser J, Ignatenko M, Iqbal MA, Lam T, Manca E, Nash WA, Saltzberg D, Stone B, Valuev V, Clare R, Gordon M, Hanson G, Si W, Wimpenny S, Branson JG, Cittolin S, Cooperstein S, Diaz D, Duarte J, Gerosa R, Giannini L, Guiang J, Kansal R, Krutelyov V, Lee R, Letts J, 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D, Berryhill J, Bhat PC, Burkett K, Butler JN, Canepa A, Cerati GB, Cheung HWK, Chlebana F, Cummings G, Dickinson J, Dutta I, Elvira VD, Feng Y, Freeman J, Gandrakota A, Gecse Z, Gray L, Green D, Grummer A, Grünendahl S, Guerrero D, Gutsche O, Harris RM, Heller R, Herwig TC, Hirschauer J, Horyn L, Jayatilaka B, Jindariani S, Johnson M, Joshi U, Klijnsma T, Klima B, Kwok KHM, Lammel S, Lincoln D, Lipton R, Liu T, Madrid C, Maeshima K, Mantilla C, Mason D, McBride P, Merkel P, Mrenna S, Nahn S, Ngadiuba J, Noonan D, Papadimitriou V, Pastika N, Pedro K, Pena C, Ravera F, Reinsvold Hall A, Ristori L, Sexton-Kennedy E, Smith N, Soha A, Spiegel L, Stoynev S, Strait J, Taylor L, Tkaczyk S, Tran NV, Uplegger L, Vaandering EW, Zoi I, Aruta C, Avery P, Bourilkov D, Cadamuro L, Chang P, Cherepanov V, Field RD, Koenig E, Kolosova M, Konigsberg J, Korytov A, Lo KH, Matchev K, Menendez N, Mitselmakher G, Muthirakalayil Madhu A, Rawal N, Rosenzweig D, Rosenzweig S, Shi K, Wang J, Adams T, Al Kadhim A, Askew A, Bower N, Habibullah R, Hagopian V, Hashmi R, Kim RS, Kim S, Kolberg T, Martinez G, Prosper H, Prova PR, Viazlo O, Wulansatiti M, Yohay R, Zhang J, Alsufyani B, Baarmand MM, Butalla S, Elkafrawy T, Hohlmann M, Kumar Verma R, Rahmani M, Adams MR, Bennett C, Cavanaugh R, Dittmer S, Escobar Franco R, Evdokimov O, Gerber CE, Hofman DJ, Lee JH, Lemos DS, Merrit AH, Mills C, Nanda S, Oh G, Ozek B, Pilipovic D, Roy T, Rudrabhatla S, Tonjes MB, Varelas N, Wang X, Ye Z, Yoo J, Alhusseini M, Blend D, Dilsiz K, Emediato L, Karaman G, Köseyan OK, Merlo JP, Mestvirishvili A, Nachtman J, Neogi O, Ogul H, Onel Y, Penzo A, Snyder C, Tiras E, Blumenfeld B, Corcodilos L, Davis J, Gritsan AV, Kang L, Kyriacou S, Maksimovic P, Roguljic M, Roskes J, Sekhar S, Swartz M, Vámi TÁ, Abreu A, Alcerro Alcerro LF, Anguiano J, Baringer P, Bean A, Flowers Z, Grove D, King J, Krintiras G, Lazarovits M, Le Mahieu C, Lindsey C, Marquez J, Minafra N, Murray M, Nickel M, Pitt M, Popescu S, Rogan C, Royon C, Salvatico R, Sanders S, Smith C, Wang Q, Wilson G, Allmond B, Ivanov A, Kaadze K, Kalogeropoulos A, Kim D, Maravin Y, Nam K, Natoli J, Roy D, Sorrentino G, Rebassoo F, Wright D, Adams E, Baden A, Baron O, Belloni A, Bethani A, Chen YM, Eno SC, Hadley NJ, Jabeen S, Kellogg RG, Koeth T, Lai Y, Lascio S, Mignerey AC, Nabili S, Palmer C, Papageorgakis C, Paranjpe MM, Wang L, Wong K, Bendavid J, Busza W, Cali IA, Chen Y, D’Alfonso M, Eysermans J, Freer C, Gomez-Ceballos G, Goncharov M, Harris P, Hoang D, Kovalskyi D, Krupa J, Lavezzo L, Lee YJ, Long K, Mironov C, Paus C, Rankin D, Roland C, Roland G, Rothman S, Shi Z, Stephans GSF, Wang J, Wang Z, Wyslouch B, Yang TJ, Crossman B, Joshi BM, Kapsiak C, Krohn M, Mahon D, Mans J, Marzocchi B, Pandey S, Revering M, Rusack R, Saradhy R, Schroeder N, Strobbe N, Wadud MA, Cremaldi LM, Bloom K, Bryson M, Claes DR, Fangmeier C, Golf F, Haza G, Hossain J, Joo C, Kravchenko I, Reed I, Siado JE, Snow GR, Tabb W, Vagnerini A, Wightman A, Yan F, Yu D, Zecchinelli AG, Agarwal G, Bandyopadhyay H, Hay L, Iashvili I, Kharchilava A, McLean C, Morris M, Nguyen D, Pekkanen J, Rappoccio S, Rejeb Sfar H, Williams A, Alverson G, Barberis E, Haddad Y, Han Y, Krishna A, Li J, Lu M, Madigan G, Morse DM, Nguyen V, Orimoto T, Parker A, Skinnari L, Tishelman-Charny A, Wang B, Wood D, Bhattacharya S, Bueghly J, Chen Z, Hahn KA, Liu Y, Miao Y, Monk DG, Schmitt MH, Taliercio A, Velasco M, Band R, Bucci R, Castells S, Cremonesi M, Das A, Goldouzian R, Hildreth M, Ho KW, Hurtado Anampa K, Jessop C, Lannon K, Lawrence J, Loukas N, Lutton L, Mariano J, Marinelli N, Mcalister I, McCauley T, Mcgrady C, Mohrman K, Moore C, Musienko Y, Nelson H, Osherson M, Ruchti R, Townsend A, Wayne M, Yockey H, Zarucki M, Zygala L, Basnet A, Bylsma B, Carrigan M, Durkin LS, Hill C, Joyce M, Lesauvage A, Nunez Ornelas M, Wei K, Winer BL, Yates BR, Addesa FM, Bouchamaoui H, Das P, Dezoort G, Elmer P, Frankenthal A, Greenberg B, Haubrich N, Higginbotham S, Kopp G, Kwan S, Lange D, Loeliger A, Marlow D, Ojalvo I, Olsen J, Stickland D, Tully C, Malik S, Bakshi AS, Barnes VE, Chandra S, Chawla R, Das S, Gu A, Gutay L, Jones M, Jung AW, Kondratyev D, Koshy AM, Liu M, Negro G, Neumeister N, Paspalaki G, Piperov S, Purohit A, Scheurer V, Schulte JF, Stojanovic M, Thieman J, Virdi AK, Wang F, Xie W, Dolen J, Parashar N, Pathak A, Acosta D, Baty A, Carnahan T, Dildick S, Ecklund KM, Fernández Manteca PJ, Freed S, Gardner P, Geurts FJM, Kumar A, Li W, Miguel Colin O, Padley BP, Redjimi R, Rotter J, Yigitbasi E, Zhang Y, Bodek A, de Barbaro P, Demina R, Dulemba JL, Fallon C, Garcia-Bellido A, Hindrichs O, Khukhunaishvili A, Parygin P, Popova E, Taus R, Van Onsem GP, Goulianos K, Chiarito B, Chou JP, Gershtein Y, Halkiadakis E, Hart A, Heindl M, Jaroslawski D, Karacheban O, Laflotte I, Lath A, Montalvo R, Nash K, Routray H, Salur S, Schnetzer S, Somalwar S, Stone R, Thayil SA, Thomas S, Vora J, Wang H, Acharya H, Ally D, Delannoy AG, Fiorendi S, Holmes T, Karunarathna N, Lee L, Nibigira E, Spanier S, Aebi D, Ahmad M, Bouhali O, Dalchenko M, Eusebi R, Gilmore J, Huang T, Kamon T, Kim H, Luo S, Malhotra S, Mueller R, Overton D, Rathjens D, Safonov A, Akchurin N, Damgov J, Hegde V, Hussain A, Kazhykarim Y, Lamichhane K, Lee SW, Mankel A, Mengke T, Muthumuni S, Peltola T, Volobouev I, Whitbeck A, Appelt E, Greene S, Gurrola A, Johns W, Kunnawalkam Elayavalli R, Melo A, Romeo F, Sheldon P, Tuo S, Velkovska J, Viinikainen J, Cardwell B, Cox B, Hakala J, Hirosky R, Ledovskoy A, Li A, Neu C, Perez Lara CE, Karchin PE, Aravind A, Banerjee S, Black K, Bose T, Dasu S, De Bruyn I, Everaerts P, Galloni C, He H, Herndon M, Herve A, Koraka CK, Lanaro A, Loveless R, Madhusudanan Sreekala J, Mallampalli A, Mohammadi A, Mondal S, Parida G, Pinna D, Savin A, Shang V, Sharma V, Smith WH, Teague D, Tsoi HF, Vetens W, Warden A, Afanasiev S, Andreev V, Andreev Y, Aushev T, Azarkin M, Babaev A, Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Bunichev V, Chadeeva M, Chekhovsky V, Chistov R, Dermenev A, Dimova T, Druzhkin D, Dubinin M, Dudko L, Ershov A, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Gribushin A, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oreshkin V, Palichik V, Perelygin V, Perfilov M, Petrushanko S, Polikarpov S, Popov V, Radchenko O, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. Search for exotic decays of the Higgs boson to a pair of pseudoscalars in the μμbb and ττbb final states. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2024; 84:493. [PMID: 38757620 PMCID: PMC11093753 DOI: 10.1140/epjc/s10052-024-12727-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 03/25/2024] [Indexed: 05/18/2024]
Abstract
A search for exotic decays of the Higgs boson (H ) with a mass of 125Ge V to a pair of light pseudoscalars a 1 is performed in final states where one pseudoscalar decays to two b quarks and the other to a pair of muons or τ leptons. A data sample of proton-proton collisions at s = 13 Te V corresponding to an integrated luminosity of 138fb - 1 recorded with the CMS detector is analyzed. No statistically significant excess is observed over the standard model backgrounds. Upper limits are set at 95% confidence level (CL ) on the Higgs boson branching fraction to μ μ b b and to τ τ b b , via a pair of a 1 s. The limits depend on the pseudoscalar mass m a 1 and are observed to be in the range (0.17-3.3) × 10 - 4 and (1.7-7.7) × 10 - 2 in the μ μ b b and τ τ b b final states, respectively. In the framework of models with two Higgs doublets and a complex scalar singlet (2HDM+S), the results of the two final states are combined to determine upper limits on the branching fraction B ( H → a 1 a 1 → ℓ ℓ b b ) at 95% CL , with ℓ being a muon or a τ lepton. For different types of 2HDM+S, upper bounds on the branching fraction B ( H → a 1 a 1 ) are extracted from the combination of the two channels. In most of the Type II 2HDM+S parameter space, B ( H → a 1 a 1 ) values above 0.23 are excluded at 95% CL for m a 1 values between 15 and 60Ge V .
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Grants
- Austrian Federal Ministry of Education, Science and Research
- Austrian Science Fund
- Belgian Fonds de la Recherche Scientifique
- Belgian Fonds voor Wetenschappelijk Onderzoek
- CNPq
- CAPES
- FAPERJ
- FAPERGS
- FAPESP
- Bulgarian Ministry of Education and Science
- Bulgarian National Science Fund
- CERN
- Chinese Academy of Sciences
- Ministry of Science and Technology
- Chinese National Natural Science Foundation of China
- Colombian Funding Agency (MINICIENCIAS)
- Croatian Ministry of Science, Education and Sport
- Croatian Science Foundation
- Research and Innovation Foundation
- SENESCYT
- Ministry of Education and Research
- Estonian Research Council via PRG780, PRG803, and PRG445
- European Regional Development Fund
- Academy of Finland
- Finnish Ministry of Education and Culture
- Helsinki Institute of Physics
- Institut National de Physique Nucléaire et de Physique des Particules
- Centre National de la Recherche Scientifique
- Commissariat à l’Énergie Atomique et aux Énergies Alternatives
- Bundesministerium für Bildung und Forschung
- Deutsche Forschungsgemeinschaft
- Helmholtz-Gemeinschaft Deutscher Forschungszentren
- General Secretariat for Research and Innovation
- National Research, Development and Innovation Office
- Department of Atomic Energy
- Department of Science and Technology
- Institute for Research in Fundamental Studies
- Science Foundation
- Istituto Nazionale di Fisica Nucleare
- Korean Ministry of Education, Science and Technology
- National Research Foundation of Korea (NRF)
- MES
- Lithuanian Academy of Sciences
- Ministry of Education
- University of Malaya
- BUAP
- CINVESTAV
- CONACYT
- LNS
- SEP
- UASLP
- MOS
- Ministry of Business, Innovation and Employment
- Pakistan Atomic Energy Commission
- Ministry of Educaton and Science
- National Science Centre
- Fundação para a Ciência e a Tecnologia, CERN/FIS-PAR/0025/2019 and CERN/FIS-INS/0032/2019
- Ministry of Education, Science and Technological Development of Serbia
- MCIN/AEI/10.13039/501100011033, ERDF “a way of making Europe”
- Fondo Europeo de Desarrollo Regional, Spain
- Plan de Ciencia, Tecnología e Innovación del Principado de Asturias
- MOSTR
- ETH Board
- ETH Zurich
- PSI
- SNF
- UniZH
- Canton Zurich
- SER
- Thailand Center of Excellence in Physics
- Institute for the Promotion of Teaching Science and Technology of Thailand
- Special Task Force for Activating Research
- National Science and Technology Development Agency of Thailand
- Scientific and Technical Research Council of Turkey
- Turkish Atomic Energy Authority
- National Academy of Sciences of Ukraine
- Science and Technology Facilities Council
- US Department of Energy
- US National Science Foundation
- Marie-Curie programme
- European Research Council and EPLANET (European Union)
- European Research Council/European Cooperation in Science and Technology), Action CA16108
- Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353 (European Union)
- Leventis Foundation
- Alfred P. Sloan Foundation
- Alexander von Humboldt Foundation
- Science Committee, project no. 22rl-037
- Belgian Federal Science Policy Office
- Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium)
- Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium)
- Belgian Fonds de la Recherche Scientifique, “Excellence of Science - EOS” - be.h project n. 30820817
- Belgian Fonds voor Wetenschappelijk Onderzoek, “Excellence of Science - EOS” - be.h project n. 30820817
- Beijing Municipal Science & Technology Commission, No. Z191100007219010
- Fundamental Research Funds for the Central Universities
- Ministry of Education, Youth and Sports (MEYS) of the Czech Republic
- Shota Rustaveli National Science Foundation
- Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy – EXC 2121 “Quantum Universe” – 390833306
- Deutsche Forschungsgemeinschaft (DFG), project number 400140256 - GRK2497
- Hellenic Foundation for Research and Innovation, Project Number 2288
- Hungarian Academy of Sciences
- New National Excellence Program - ÚNKP, the NKFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64
- Council of Scientific and Industrial Research, India
- Latvian Council of Science
- Ministy of Education and Science, project no. 2022/WK/14
- National Science Center, Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552
- Fundação para a Ciência e a Tecnologia, CEECIND/01334/2018
- National Priorities Research Program by Qatar National Research Fund
- Ministry of Science and Higher Education, project no. FSWU-2023-0073 and FSWW-2020-0008
- Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2017-0765 and projects PID2020-113705RB, PID2020-113304RB, PID2020-116262RB and PID2020-113341RB-I00
- Programa Severo Ochoa del Principado de Asturias
- Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand)
- CUAASC
- Kavli Foundation
- Nvidia Corporation
- Welch Foundation, contract C-1845
- Weston Havens Foundation
- Institut für Hochenergiephysik (HEPHY) using the Cloud Infrastructure Platform (CLIP), Vienna
- Inter-University Institute for High Energies, Brussels
- Université Catholique de Louvain, Louvain-la-Neuve
- São Paulo Research and Analysis Center, São Paulo
- Universidade do Estado do Rio de Janeiro, Rio de Janeiro
- University of Sofia, Sofia
- Institute of High Energy Physics of the Chinese Academy of Sciences, Beijing
- National Institute of Chemical Physics and Biophysics, Tallinn
- Helsinki Institute of Physics, Helsinki
- Grille de Recherche d’Ile de France (GRIF), Institut de recherche sur les lois fondamentales de l’Univers, CEA, Université Paris-Saclay, Gif-sur-Yvette, France and Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris
- Institut de recherche sur les lois fondamentales de l’Univers, CEA, Université Paris-Saclay, Gif-sur-Yvette
- Institut national de physique nucléaire et de physique des particules, IN2P3, Villeurbanne
- Institut Pluridisciplinaire Hubert Curien (IPHC), Strasbourg
- Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau
- Deutsches Elektronen-Synchrotron, Hamburg
- Karlsruher Institut für Technologie, Karlsruhe
- RWTH Aachen University, Aachen
- University of Ioánnina, Ioánnina
- Wigner Research Centre for Physics, Budapest
- Tata Institute of Fundamental Research, Mumbai
- INFN CNAF, Bologna
- INFN Sezione di Bari, Università di Bari, Politecnico di Bari, Bari
- INFN Sezione di Pisa, Università di Pisa, Scuola Normale Superiore di Pisa, Pisa
- INFN Sezione di Roma, Sapienza Università di Roma, Rome
- INFN Sezione di Trieste, Università di Trieste, Trieste
- Laboratori Nazionali di Legnaro, Legnaro
- Kyungpook National University, Daegu
- National Centre for Physics, Quaid-I-Azam University, Islamabad
- Akademickie Centrum Komputerowe Cyfronet AGH, Krakow
- National Centre for Nuclear Research, Swierk
- Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa
- Korea Institute of Science and Technology Information (KISTI), Daejeon
- Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid
- Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander
- Port d’Informació Científica, Bellaterra
- CERN, European Organization for Nuclear Research, Geneva
- CSCS - Swiss National Supercomputing Centre, Lugano
- Instrumentation and Detector Consortium, Taipei
- National Center for High-performance Computing (NCHC), Hsinchu City
- Middle East Technical University, Physics Department, Ankara
- National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov
- GridPP, Brunel University, Uxbridge
- GridPP, Imperial College, London
- GridPP, Queen Mary University of London, London
- GridPP, Royal Holloway, University of London, London
- GridPP, Rutherford Appleton Laboratory, Didcot
- GridPP, University of Bristol, Bristol
- GridPP, University of Glasgow, Glasgow
- GridPP, University of Oxford, Oxford
- Baylor University, Waco
- California Institute of Technology, Pasadena
- Fermi National Accelerator Laboratory, Batavia
- Massachusetts Institute of Technology, Cambridge
- National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility, Berkeley
- Open Science Grid (OSG) Consortium
- Pittsburgh Supercomputing Center (PSC), Pittsburgh
- Purdue University, West Lafayette
- San Diego Supercomputer Center (SDSC), La Jolla
- Texas Advanced Computing Center (TACC), Austin
- University of California, San Diego, La Jolla
- University of Colorado Boulder, Boulder
- University of Florida, Gainesville
- University of Nebraska-Lincoln, Lincoln
- University of Wisconsin - Madison, Madison
- Vanderbilt University, Nashville
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Chen W, Liu X, Wan P, Chen Z, Chen Y. Anti-artifacts techniques for neural recording front-ends in closed-loop brain-machine interface ICs. Front Neurosci 2024; 18:1393206. [PMID: 38784093 PMCID: PMC11111950 DOI: 10.3389/fnins.2024.1393206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024] Open
Abstract
In recent years, thanks to the development of integrated circuits, clinical medicine has witnessed significant advancements, enabling more efficient and intelligent treatment approaches. Particularly in the field of neuromedical, the utilization of brain-machine interfaces (BMI) has revolutionized the treatment of neurological diseases such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. The BMI acquires neural signals via recording circuits and analyze them to regulate neural stimulator circuits for effective neurological treatment. However, traditional BMI designs, which are often isolated, have given way to closed-loop brain-machine interfaces (CL-BMI) as a contemporary development trend. CL-BMI offers increased integration and accelerated response speed, marking a significant leap forward in neuromedicine. Nonetheless, this advancement comes with its challenges, notably the stimulation artifacts (SA) problem inherent to the structural characteristics of CL-BMI, which poses significant challenges on the neural recording front-ends (NRFE) site. This paper aims to provide a comprehensive overview of technologies addressing artifacts in the NRFE site within CL-BMI. Topics covered will include: (1) understanding and assessing artifacts; (2) exploring the impact of artifacts on traditional neural recording front-ends; (3) reviewing recent technological advancements aimed at addressing artifact-related issues; (4) summarizing and classifying the aforementioned technologies, along with an analysis of future trends.
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Liu B, Tian G, Han R, Shi F, Sun H, Chen Z, Zhang Z, Li Q, Luo P. Excitation functions for fast neutron induced reactions on iron and lead. Appl Radiat Isot 2024; 207:111274. [PMID: 38447263 DOI: 10.1016/j.apradiso.2024.111274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 02/12/2024] [Accepted: 02/29/2024] [Indexed: 03/08/2024]
Abstract
Cross sections of the 54Fe(n,p)54Mn, 54Fe(n,α)51Cr, 56Fe(n,p)56Mn and 204Pb (n,2n)203Pb reactions induced by D-T neutrons were obtained with activation method and γ-ray spectrometry technique. Experimental values measured in this work are consistent with most of the previous literature data. These reactions cross sections were theoretically calculated by using the TALYS-1.96 and EMPIRE-3.2.3 codes from threshold up to 20 MeV, and significant discrepancies were found between calculated results and experiment data. In addition, experimental values are compared with evaluated nuclear data of the CENDL-3.2, ENDF/B-VIII.0, JENDL-5, BROND-3.1 and JEFF-3.3 libraries, and significant difference was found for the 54Fe(n,α)51Cr reaction in ENDF/B-VIII.0 library but not for other reactions.
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Chen C, Meng L, Cao L, Zhang D, An S, Liu L, Wang J, Li G, Pan T, Shen J, Chen Z, Shi Z, Lai Z, Han Y. Phase Engineering of Zirconium MOFs Enables Efficient Osmotic Energy Conversion: Structural Evolution Unveiled by Direct Imaging. J Am Chem Soc 2024; 146:11855-11865. [PMID: 38634945 DOI: 10.1021/jacs.4c00716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Creating structural defects in a controlled manner within metal-organic frameworks (MOFs) poses a significant challenge for synthesis, and concurrently, identifying the types and distributions of these defects is also a formidable task for characterization. In this study, we demonstrate that by employing 2-sulfonylterephthalic acid as the ligand for synthesizing Zr (or Hf)-based MOFs, a crystal phase transformation from the common fcu topology to the rare jmt topology can be easily facilitated using a straightforward mixed-solvent strategy. The jmt phase, characterized by an extensively open framework, can be considered a derivative of the fcu phase, generated through the introduction of missing-cluster defects. We have explicitly identified both MOF phases, their intermediate states, and the novel core-shell structures they form using ultralow-dose high-resolution transmission electron microscopy. In addition to facilitating phase engineering, the incorporation of sulfonic groups in MOFs imparts ionic selectivity, making them applicable for osmotic energy harvesting through mixed matrix membrane fabrication. The membrane containing the jmt-phase MOF exhibits an exceptionally high peak power density of 10.08 W m-2 under a 50-fold salinity gradient (NaCl: 0.5 M|0.01 M), which surpasses the threshold of 5 W m-2 for commercial applications and can be attributed to the combination of large pore size, extensive porosity, and abundant sulfonic groups in this novel MOF material.
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Pan S, Wei P, Li Y, Chen Z, Peng D, Wang L, Liu C, Hong B, Zhang F, Li Y. Identification of Meloidogyne Species on Traditional Chinese Medicine Plants in the Qinling Mountain Area of China and Their Aggressiveness to Different Medicinal Herbs. PLANT DISEASE 2024; 108:1202-1210. [PMID: 37849284 DOI: 10.1094/pdis-01-23-0148-re] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
Root-knot nematodes (Meloidogyne spp.) are plant-parasitic nematodes that cause serious damage worldwide. There are many species of traditional Chinese medicine (TCM) plants, but only a few have been reported to be infected by Meloidogyne species. From 2020 to 2022, a survey was conducted in the Qinling mountain area, which is the main production region of TCM plants in China. Obvious galling symptoms were observed on the root systems of 15 species of TCM plants. Females were collected from diverse diseased TCM plants and subsequently identified at morphological and molecular levels. Among the 20 diseased root samples collected, Meloidogyne hapla populations were identified in 12 samples (60%), and M. incognita populations were identified in eight samples (40%). Among the 15 species of diseased TCM plants, eight species, namely, Scutellaria baicalensis, Leonurus japonicus, Dioscorea zingiberensis, Cornus officinalis, Viola philippica, Achyranthes bidentata, Senecio scandens, and Plantago depressa, were reported to be infected by Meloidogyne species for the first time. The host status of five species of TCM plants for two M. hapla isolates and one M. incognita isolate from TCM plants in this study was then evaluated. Differences in TCM plants' response to nematode infection were apparent when susceptibility was evaluated by the egg counts per gram of fresh root and the reproduction factor of the nematodes. Among the five species of TCM plants tested, Salvia miltiorrhiza and Gynostemma pentaphyllum were the most susceptible, while S. baicalensis and V. philippica were not considered suitable hosts for M. hapla or M. incognita.
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Wu Y, Deng W, Li K, Wang X, Liu B, Li J, Chen Z, Zhang Y. A Spiking Artificial Vision Architecture Based on Fully Emulating the Human Vision. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2312094. [PMID: 38320173 DOI: 10.1002/adma.202312094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/29/2024] [Indexed: 02/08/2024]
Abstract
Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this goal by the continuous processing of massive image frames and executing intricate algorithms, thereby expending substantial computational power and energy. In contrast, biological data processing, based on event-triggered spiking, has higher efficiency and lower energy consumption. Here, this work proposes an artificial vision architecture consisting of spiking photodetectors and artificial synapses, closely mirroring the intricacies of the human visual system. Distinct from previously reported techniques, the photodetector is self-powered and event-triggered, outputting light-modulated spiking signals directly, thereby fulfilling the imperative for always-on with low-power consumption. With the spiking signals processing through the integrated synapse units, recognition of graphics, gestures, and human action has been implemented, illustrating the potent image processing capabilities inherent within this architecture. The results prove the 90% accuracy rate in human action recognition within a mere five epochs utilizing a rudimentary artificial neural network. This novel architecture, grounded in spiking photodetectors, offers a viable alternative to the extant models of always-on low-power artificial vision system.
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Zhang J, Wang S, Jiang Z, Chen Z, Bai X. CD-Net: Cascaded 3D Dilated convolutional neural network for pneumonia lesion segmentation. Comput Biol Med 2024; 173:108311. [PMID: 38513395 DOI: 10.1016/j.compbiomed.2024.108311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/22/2024] [Accepted: 03/12/2024] [Indexed: 03/23/2024]
Abstract
COVID-19 is a global pandemic that has caused significant global, social, and economic disruption. To effectively assist in screening and monitoring diagnosed cases, it is crucial to accurately segment lesions from Computer Tomography (CT) scans. Due to the lack of labeled data and the presence of redundant parameters in 3D CT, there are still significant challenges in diagnosing COVID-19 in related fields. To address the problem, we have developed a new model called the Cascaded 3D Dilated convolutional neural network (CD-Net) for directly processing CT volume data. To reduce memory consumption when cutting volume data into small patches, we initially design a cascade architecture in CD-Net to preserve global information. Then, we construct a Multi-scale Parallel Dilated Convolution (MPDC) block to aggregate features of different sizes and simultaneously reduce the parameters. Moreover, to alleviate the shortage of labeled data, we employ classical transfer learning, which requires only a small amount of data while achieving better performance. Experimental results conducted on the different public-available datasets verify that the proposed CD-Net has reduced the negative-positive ratio and outperformed other existing segmentation methods while requiring less data.
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Abbasi R, Ackermann M, Adams J, Agarwalla SK, Aguilar JA, Ahlers M, Alameddine JM, Amin NM, Andeen K, Anton G, Argüelles C, Ashida Y, Athanasiadou S, Axani SN, Bai X, Balagopal VA, Baricevic M, Barwick SW, Basu V, Bay R, Beatty JJ, Becker Tjus J, Beise J, Bellenghi C, Benning C, BenZvi S, Berley D, Bernardini E, Besson DZ, Blaufuss E, Blot S, Bontempo F, Book JY, Boscolo Meneguolo C, Böser S, Botner O, Böttcher J, Bourbeau E, Braun J, Brinson B, Brostean-Kaiser J, Burley RT, Busse RS, Butterfield D, Campana MA, Carloni K, Carnie-Bronca EG, Chattopadhyay S, Chau N, Chen C, Chen Z, Chirkin D, Choi S, Clark BA, Classen L, Coleman A, Collin GH, Connolly A, Conrad JM, Coppin P, Correa P, Cowen DF, Dave P, De Clercq C, DeLaunay JJ, Delgado D, Deng S, Deoskar K, Desai A, Desiati P, de Vries KD, de Wasseige G, DeYoung T, Diaz A, Díaz-Vélez JC, Dittmer M, Domi A, Dujmovic H, DuVernois MA, Ehrhardt T, Eller P, Ellinger E, El Mentawi S, Elsässer D, Engel R, Erpenbeck H, Evans J, Evenson PA, Fan KL, Fang K, Farrag K, Fazely AR, Feigl N, Fiedlschuster S, Fienberg AT, Finley C, Fischer L, Fox D, Franckowiak A, Fritz A, Fürst P, Gallagher J, Ganster E, Garcia A, Gerhardt L, Ghadimi A, Glaser C, Glauch T, Glüsenkamp T, Goehlke N, Gonzalez JG, Goswami S, Grant D, Gray SJ, Gries O, Griffin S, Griswold S, Groth KM, Günther C, Gutjahr P, Haack C, Hallgren A, Halliday R, Halve L, Halzen F, Hamdaoui H, Ha Minh M, Hanson K, Hardin J, Harnisch AA, Hatch P, Haungs A, Helbing K, Hellrung J, Henningsen F, Heuermann L, Heyer N, Hickford S, Hidvegi A, Hill C, Hill GC, Hoffman KD, Hori S, Hoshina K, Hou W, Huber T, Hultqvist K, Hünnefeld M, Hussain R, Hymon K, In S, Ishihara A, Jacquart M, Janik O, Jansson M, Japaridze GS, Jeong M, Jin M, Jones BJP, Kang D, Kang W, Kang X, Kappes A, Kappesser D, Kardum L, Karg T, Karl M, Karle A, Katz U, Kauer M, Kelley JL, Khatee Zathul A, Kheirandish A, Kiryluk J, Klein SR, Kochocki A, Koirala R, Kolanoski H, Kontrimas T, Köpke L, Kopper C, Koskinen DJ, Koundal P, Kovacevich M, Kowalski M, Kozynets T, Krishnamoorthi J, Kruiswijk K, Krupczak E, Kumar A, Kun E, Kurahashi N, Lad N, Lagunas Gualda C, Lamoureux M, Larson MJ, Latseva S, Lauber F, Lazar JP, Lee JW, Leonard DeHolton K, Leszczyńska A, Lincetto M, Liu QR, Liubarska M, Lohfink E, Love C, Lozano Mariscal CJ, Lucarelli F, Luszczak W, Lyu Y, Madsen J, Mahn KBM, Makino Y, Manao E, Mancina S, Marie Sainte W, Mariş IC, Marka S, Marka Z, Marsee M, Martinez-Soler I, Maruyama R, Mayhew F, McElroy T, McNally F, Mead JV, Meagher K, Mechbal S, Medina A, Meier M, Merckx Y, Merten L, Micallef J, Mitchell J, Montaruli T, Moore RW, Morii Y, Morse R, Moulai M, Mukherjee T, Naab R, Nagai R, Nakos M, Naumann U, Necker J, Negi A, Neumann M, Niederhausen H, Nisa MU, Noell A, Novikov A, Nowicki SC, Obertacke Pollmann A, O'Dell V, Oehler M, Oeyen B, Olivas A, Orsoe R, Osborn J, O'Sullivan E, Pandya H, Pankova DV, Park N, Parker GK, Paudel EN, Paul L, Pérez de Los Heros C, Peterson J, Philippen S, Pizzuto A, Plum M, Pontén A, Popovych Y, Prado Rodriguez M, Pries B, Procter-Murphy R, Przybylski GT, Raab C, Rack-Helleis J, Rawlins K, Rechav Z, Rehman A, Reichherzer P, Renzi G, Resconi E, Reusch S, Rhode W, Riedel B, Rifaie A, Roberts EJ, Robertson S, Rodan S, Roellinghoff G, Rongen M, Rott C, Ruhe T, Ruohan L, Ryckbosch D, Safa I, Saffer J, Salazar-Gallegos D, Sampathkumar P, Sanchez Herrera SE, Sandrock A, Santander M, Sarkar S, Sarkar S, Savelberg J, Savina P, Schaufel M, Schieler H, Schindler S, Schlickmann L, Schlüter B, Schlüter F, Schmeisser N, Schmidt T, Schneider J, Schröder FG, Schumacher L, Schwefer G, Sclafani S, Seckel D, Seikh M, Seunarine S, Shah R, Sharma A, Shefali S, Shimizu N, Silva M, Skrzypek B, Smithers B, Snihur R, Soedingrekso J, Søgaard A, Soldin D, Soldin P, Sommani G, Spannfellner C, Spiczak GM, Stamatikos M, Stanev T, Stezelberger T, Stürwald T, Stuttard T, Sullivan GW, Taboada I, Ter-Antonyan S, Thiesmeyer M, Thompson WG, Thwaites J, Tilav S, Tollefson K, Tönnis C, Toscano S, Tosi D, Trettin A, Tung CF, Turcotte R, Twagirayezu JP, Ty B, Unland Elorrieta MA, Upadhyay AK, Upshaw K, Valtonen-Mattila N, Vandenbroucke J, van Eijndhoven N, Vannerom D, van Santen J, Vara J, Veitch-Michaelis J, Venugopal M, Vereecken M, Verpoest S, Veske D, Vijai A, Walck C, Weaver C, Weigel P, Weindl A, Weldert J, Wen AY, Wendt C, Werthebach J, Weyrauch M, Whitehorn N, Wiebusch CH, Willey N, Williams DR, Witthaus L, Wolf A, Wolf M, Wrede G, Xu XW, Yanez JP, Yildizci E, Yoshida S, Young R, Yu F, Yu S, Zhang Z, Zhelnin P, Zilberman P, Zimmerman M. Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube. PHYSICAL REVIEW LETTERS 2024; 132:151001. [PMID: 38682982 DOI: 10.1103/physrevlett.132.151001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 02/15/2024] [Accepted: 02/29/2024] [Indexed: 05/01/2024]
Abstract
We report on a measurement of astrophysical tau neutrinos with 9.7 yr of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate ν_{τ} events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent ν_{τ} energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from π^{±}/K^{±} decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-ν_{τ} astrophysical neutrinos. Thus, we rule out the absence of astrophysical ν_{τ} at the 5σ level. The measured astrophysical ν_{τ} flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations.
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Xu SL, Chen Z, Yang J, Fan ZQ, Liu T, Zhang XT, Zeng BQ, Xing XQ. [Effect of SHP-1 knockout in airway epithelial cells on emphysema phenotype in chronic obstructive pulmonary disease in mice]. ZHONGHUA JIE HE HE HU XI ZA ZHI = ZHONGHUA JIEHE HE HUXI ZAZHI = CHINESE JOURNAL OF TUBERCULOSIS AND RESPIRATORY DISEASES 2024; 47:339-345. [PMID: 38599809 DOI: 10.3760/cma.j.cn112147-20231114-00309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
Objective: To construct and characterize conditional Src homology region 2 protein tyrosine phosphatase 1 (SHP-1) knockout mice in airway epithelial cells and to observe the effect of defective SHP-1 expression in airway epithelial cells on the emphysema phenotype in chronic obstructive pulmonary disease (COPD). Methods: To detect the expression of SHP-1 in the airway epithelium of COPD patients. CRISPR/Cas9 technology was used to construct SHP-1flox/flox transgenic mice, which were mated with airway epithelial Clara protein 10-cyclase recombinase and estrogen receptor fusion transgenic mice (CC10-CreER+/+), and after intraperitoneal injection of tamoxifen, airway epithelial SHP-1 knockout mice were obtained (SHP-1flox/floxCC10-CreER+/-, SHP-1Δ/Δ). Mouse tail and lung tissue DNA was extracted and PCR amplified to discriminate the genotype of the mice; the knockout effect of SHP-1 gene in airway epithelial cells was verified by qRT-PCR, Western blotting, and immunofluorescence. In addition, an emphysema mouse model was constructed using elastase to assess the severity of emphysema in each group of mice. Results: Airway epithelial SHP-1 was significantly downregulated in COPD patients. Genotyping confirmed that SHP-1Δ/Δ mice expressed CC10-CreER and SHP-1-flox. After tamoxifen induction, we demonstrated the absence of SHP-1 protein expression in airway epithelial cells of SHP-1Δ/Δ mice at the DNA, RNA, and protein levels, indicating that airway epithelial cell-specific SHP-1 knockout mice had been successfully constructed. In the emphysema animal model, SHP-1Δ/Δ mice had a more severe emphysema phenotype compared with the control group, which was manifested by disorganization of alveolar structure in lung tissue and rupture and fusion of alveolar walls to form pulmonary alveoli. Conclusions: The present study successfully established and characterized the SHP-1 knockout mouse model of airway epithelial cells, which provides a new experimental tool for the in-depth elucidation of the role of SHP-1 in the emphysema process of COPD and its mechanism.
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Liang YC, Wang L, Zhang QF, Chen Z. [A review of cross-cultural adaptation as well as reliability and validity studies on self-reported voice questionnaires]. ZHONGHUA ER BI YAN HOU TOU JING WAI KE ZA ZHI = CHINESE JOURNAL OF OTORHINOLARYNGOLOGY HEAD AND NECK SURGERY 2024; 59:399-404. [PMID: 38622026 DOI: 10.3760/cma.j.cn115330-20231026-00170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Liu H, Duan J, Zeng P, Shi M, Zeng J, Chen S, Gong Z, Chen Z, Qin J, Chen Z. Intelligently Quantifying the Entire Irregular Dental Structure. J Dent Res 2024; 103:378-387. [PMID: 38372132 DOI: 10.1177/00220345241226871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2024] Open
Abstract
Quantitative analysis of irregular anatomical structures is crucial in oral medicine, but clinicians often typically measure only several representative indicators within the structure as references. Deep learning semantic segmentation offers the potential for entire quantitative analysis. However, challenges persist, including segmentation difficulties due to unclear boundaries and acquiring measurement landmarks for clinical needs in entire quantitative analysis. Taking the palatal alveolar bone as an example, we proposed an artificial intelligence measurement tool for the entire quantitative analysis of irregular dental structures. To expand the applicability, we have included lightweight networks with fewer parameters and lower computational demands. Our approach finally used the lightweight model LU-Net, addressing segmentation challenges caused by unclear boundaries through a compensation module. Additional enamel segmentation was conducted to establish a measurement coordinate system. Ultimately, we presented the entire quantitative information within the structure in a manner that meets clinical needs. The tool achieved excellent segmentation results, manifested by high Dice coefficients (0.934 and 0.949), intersection over union (0.888 and 0.907), and area under the curve (0.943 and 0.949) for palatal alveolar bone and enamel in the test set. In subsequent measurements, the tool visualizes the quantitative information within the target structure by scatter plots. When comparing the measurements against representative indicators, the tool's measurement results show no statistically significant difference from the ground truth, with small mean absolute error, root mean squared error, and errors interval. Bland-Altman plots and intraclass correlation coefficients indicate the satisfactory agreement compared with manual measurements. We proposed a novel intelligent approach to address the entire quantitative analysis of irregular image structures in the clinical setting. This contributes to enabling clinicians to swiftly and comprehensively grasp structural features, facilitating the design of more personalized treatment plans for different patients, enhancing clinical efficiency and treatment success rates in turn.
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Hayrapetyan A, Tumasyan A, Adam W, Andrejkovic JW, Bergauer T, Chatterjee S, Damanakis K, Dragicevic M, Escalante Del Valle A, Hussain PS, Jeitler M, Krammer N, Liko D, Mikulec I, Schieck J, Schöfbeck R, Schwarz D, Sonawane M, Templ S, Waltenberger W, Wulz CE, Darwish MR, Janssen T, Van Mechelen P, Bols ES, D'Hondt J, Dansana S, De Moor A, Delcourt M, El Faham H, Lowette S, Makarenko I, Müller D, Sahasransu AR, Tavernier S, Tytgat M, Van Putte S, Vannerom D, Clerbaux B, De Lentdecker G, Favart L, Hohov D, Jaramillo J, Khalilzadeh A, Lee K, Mahdavikhorrami M, Malara A, Paredes S, Pétré L, Postiau N, Thomas L, Vanden Bemden M, Vander Velde C, Vanlaer P, De Coen M, Dobur D, Hong Y, Knolle J, Lambrecht L, Mestdach G, Rendón C, Samalan A, Skovpen K, Van Den Bossche N, Wezenbeek L, Benecke A, Bruno G, Caputo C, Delaere C, Donertas IS, Giammanco A, Jaffel K, Jain S, Lemaitre V, Lidrych J, Mastrapasqua P, Mondal K, Tran TT, Wertz S, Alves GA, Coelho E, Hensel C, Menezes De Oliveira T, Moraes A, Rebello Teles P, Soeiro M, Aldá Júnior WL, Alves Gallo Pereira M, Barroso Ferreira Filho M, Brandao Malbouisson H, Carvalho W, Chinellato J, Da Costa EM, Da Silveira GG, De Jesus Damiao D, Fonseca De Souza S, Martins J, Mora Herrera C, Mota Amarilo K, Mundim L, Nogima H, Santoro A, Silva Do Amaral SM, Sznajder A, Thiel M, Vilela Pereira A, Bernardes CA, Calligaris L, Tomei TRFP, Gregores EM, Mercadante PG, Novaes SF, Orzari B, Padula SS, Aleksandrov A, Antchev G, Hadjiiska R, Iaydjiev P, Misheva M, Shopova M, Sultanov G, Dimitrov A, Ivanov T, Litov L, Pavlov B, Petkov P, Petrov A, Shumka E, Keshri S, Thakur S, Cheng T, Guo Q, Javaid T, Mittal M, Yuan L, Bauer G, Hu Z, Yi K, Chen GM, Chen HS, Chen M, Iemmi F, Jiang CH, Kapoor A, Liao H, Liu ZA, Monti F, Shahzad MA, Sharma R, Song JN, Tao J, Wang C, Wang J, Wang Z, Zhang H, Agapitos A, Ban Y, Guan Z, Levin A, Li C, Li Q, Lyu X, Mao Y, Qian SJ, Sun X, Wang D, Yang H, Zhou C, You Z, Lu N, Leggat D, Okawa H, Zhang Y, Lin Z, Lu C, Xiao M, Avila C, Barbosa Trujillo DA, Cabrera A, Florez C, Fraga J, Reyes Vega JA, Mejia Guisao J, Ramirez F, Rodriguez M, Ruiz Alvarez JD, Giljanovic D, Godinovic N, Lelas D, Sculac A, Kovac M, Sculac T, Bargassa P, Brigljevic V, Chitroda BK, Ferencek D, Mishra S, Starodumov A, Susa T, Attikis A, Christoforou K, Konstantinou S, Mousa J, Nicolaou C, Ptochos F, Razis PA, Rykaczewski H, Saka H, Stepennov A, Finger M, Finger M, Kveton A, Ayala E, Carrera Jarrin E, Abdelalim AA, Salama E, Abdullah Al-Mashad M, Mahmoud MA, Dewanjee RK, Ehataht K, Kadastik M, Lange T, Nandan S, Nielsen C, Pata J, Raidal M, Tani L, Veelken C, Kirschenmann H, Osterberg K, Voutilainen M, Bharthuar S, Brücken E, Garcia F, Havukainen J, Kallonen KTS, Kim MS, Kinnunen R, Lampén T, Lassila-Perini K, Lehti S, Lindén T, Lotti M, Martikainen L, Myllymäki M, Rantanen MM, Siikonen H, Tuominen E, Tuominiemi J, Luukka P, Petrow H, Tuuva T, Besancon M, Couderc F, Dejardin M, Denegri D, Faure JL, Ferri F, Ganjour S, Gras P, Hamel 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M, Stadie H, Steinbrück G, Tews A, Wolf M, Brommer S, Burkart M, Butz E, Chwalek T, Dierlamm A, Droll A, Faltermann N, Giffels M, Gottmann A, Hartmann F, Hofsaess R, Horzela M, Husemann U, Klute M, Koppenhöfer R, Link M, Lintuluoto A, Maier S, Mitra S, Mormile M, Müller T, Neukum M, Oh M, Quast G, Rabbertz K, Regnery B, Shadskiy N, Shvetsov I, Simonis HJ, Trevisani N, Ulrich R, van der Linden J, Von Cube RF, Wassmer M, Wieland S, Wittig F, Wolf R, Wunsch S, Zuo X, Anagnostou G, Assiouras P, Daskalakis G, Kyriakis A, Papadopoulos A, Stakia A, Karasavvas D, Kontaxakis P, Melachroinos G, Panagiotou A, Papavergou I, Paraskevas I, Saoulidou N, Theofilatos K, Tziaferi E, Vellidis K, Zisopoulos I, Bakas G, Chatzistavrou T, Karapostoli G, Kousouris K, Papakrivopoulos I, Siamarkou E, Tsipolitis G, Zacharopoulou A, Adamidis K, Bestintzanos I, Evangelou I, Foudas C, Gianneios P, Kamtsikis C, Katsoulis P, Kokkas P, Kosmoglou Kioseoglou PG, Manthos N, Papadopoulos I, Strologas J, Bartók M, Hajdu C, Horvath D, Sikler F, Veszpremi V, Csanád M, Farkas K, Gadallah MMA, Kadlecsik Á, Major P, Mandal K, Pásztor G, Rádl AJ, Veres GI, Raics P, Ujvari B, Zilizi G, Bencze G, Czellar S, Karancsi J, Molnar J, Szillasi Z, Csorgo T, Nemes F, Novak T, Babbar J, Bansal S, Beri SB, Bhatnagar V, Chaudhary G, Chauhan S, Dhingra N, Gupta R, Kaur A, Kaur A, Kaur H, Kaur M, Kumar S, Kumari P, Meena M, Sandeep K, Sheokand T, Singh JB, Singla A, Ahmed A, Bhardwaj A, Chhetri A, Choudhary BC, Kumar A, Naimuddin M, Ranjan K, Saumya S, Acharya S, Baradia S, Barman S, Bhattacharya S, Bhowmik D, Dutta S, Dutta S, Gomber B, Palit P, Saha G, Sahu B, Sarkar S, Ameen MM, Behera PK, Behera SC, Chatterjee S, Jana P, Kalbhor P, Komaragiri JR, Kumar D, Panwar L, Pradhan R, Pujahari PR, Saha NR, Sharma A, Sikdar AK, Verma S, Aziz T, Das I, Dugad S, Kumar M, Mohanty GB, Suryadevara P, Bala A, Banerjee S, Chatterjee RM, Guchait M, Karmakar S, Kumar S, Majumder G, Mazumdar K, Mukherjee S, Thachayath A, Bahinipati S, Das 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Mattia A, Potenza R, Tricomi A, Tuve C, Barbagli G, Bardelli G, Camaiani B, Cassese A, Ceccarelli R, Ciulli V, Civinini C, D'Alessandro R, Focardi E, Latino G, Lenzi P, Lizzo M, Meschini M, Paoletti S, Papanastassiou A, Sguazzoni G, Viliani L, Benussi L, Bianco S, Meola S, Piccolo D, Chatagnon P, Ferro F, Robutti E, Tosi S, Benaglia A, Boldrini G, Brivio F, Cetorelli F, De Guio F, Dinardo ME, Dini P, Gennai S, Ghezzi A, Govoni P, Guzzi L, Lucchini MT, Malberti M, Malvezzi S, Massironi A, Menasce D, Moroni L, Paganoni M, Pedrini D, Pinolini BS, Ragazzi S, Redaelli N, Tabarelli de Fatis T, Zuolo D, Buontempo S, Cagnotta A, Carnevali F, Cavallo N, De Iorio A, Fabozzi F, Iorio AOM, Lista L, Paolucci P, Rossi B, Sciacca C, Ardino R, Azzi P, Bacchetta N, Bisello D, Bortignon P, Bragagnolo A, Carlin R, Checchia P, Dorigo T, Fanzago F, Gasparini F, Gonella F, Grosso G, Layer L, Lusiani E, Margoni M, Meneguzzo AT, Migliorini M, Pazzini J, Ronchese P, Rossin R, Simonetto F, Strong G, Tosi M, 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Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Bunichev V, Chekhovsky V, Chistov R, Danilov M, Dermenev A, Dimova T, Druzhkin D, Dubinin M, Dudko L, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Gribushin A, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Lukina O, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oreshkin V, Palichik V, Perelygin V, Petrushanko S, Polikarpov S, Popov V, Radchenko O, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Snigirev A, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. Observation of WWγ Production and Search for Hγ Production in Proton-Proton Collisions at sqrt[s]=13 TeV. PHYSICAL REVIEW LETTERS 2024; 132:121901. [PMID: 38579207 DOI: 10.1103/physrevlett.132.121901] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 01/31/2024] [Indexed: 04/07/2024]
Abstract
The observation of WWγ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138 fb^{-1} is presented. The observed (expected) significance is 5.6 (5.1) standard deviations. Events are selected by requiring exactly two leptons (one electron and one muon) of opposite charge, moderate missing transverse momentum, and a photon. The measured fiducial cross section for WWγ is 5.9±0.8(stat)±0.8(syst)±0.7(modeling) fb, in agreement with the next-to-leading order quantum chromodynamics prediction. The analysis is extended with a search for the associated production of the Higgs boson and a photon, which is generated by a coupling of the Higgs boson to light quarks. The result is used to constrain the Higgs boson couplings to light quarks.
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Albrow M, Alyari M, Amram O, Apollinari G, Apresyan A, Bauerdick LAT, Berry D, Berryhill J, Bhat PC, Burkett K, Butler JN, Canepa A, Cerati GB, Cheung HWK, Chlebana F, Cummings G, Dickinson J, Dutta I, Elvira VD, Feng Y, Freeman J, Gandrakota A, Gecse Z, Gray L, Green D, Grünendahl S, Guerrero D, Gutsche O, Harris RM, Heller R, Herwig TC, Hirschauer J, Horyn L, Jayatilaka B, Jindariani S, Johnson M, Joshi U, Klijnsma T, Klima B, Kwok KHM, Lammel S, Lincoln D, Lipton R, Liu T, Madrid C, Maeshima K, Mantilla C, Mason D, McBride P, Merkel P, Mrenna S, Nahn S, Ngadiuba J, Noonan D, Papadimitriou V, Pastika N, Pedro K, Pena C, Ravera F, Reinsvold Hall A, Ristori L, Sexton-Kennedy E, Smith N, Soha A, Spiegel L, Stoynev S, Taylor L, Tkaczyk S, Tran NV, Uplegger L, Vaandering EW, Zoi I, Aruta C, Avery P, Bourilkov D, Cadamuro L, Chang P, Cherepanov V, Field RD, Koenig E, Kolosova M, Konigsberg J, Korytov A, Lo KH, Matchev K, Menendez N, Mitselmakher G, Muthirakalayil Madhu A, Rawal N, Rosenzweig D, Rosenzweig S, Shi K, Wang J, Adams T, Al Kadhim A, Askew A, Bower N, Habibullah R, Hagopian V, Hashmi R, Kim RS, Kim S, Kolberg T, Martinez G, Prosper H, Prova PR, Viazlo O, Wulansatiti M, Yohay R, Zhang J, Alsufyani B, Baarmand MM, Butalla S, Elkafrawy T, Hohlmann M, Kumar Verma R, Rahmani M, Adams MR, Bennett C, Cavanaugh R, Dittmer S, Escobar Franco R, Evdokimov O, Gerber CE, Hofman DJ, Lee JH, Lemos DS, Merrit AH, Mills C, Nanda S, Oh G, Ozek B, Pilipovic D, Roy T, Rudrabhatla S, Tonjes MB, Varelas N, Wang X, Ye Z, Yoo J, Alhusseini M, Blend D, Dilsiz K, Emediato L, Karaman G, Köseyan OK, Merlo JP, Mestvirishvili A, Nachtman J, Neogi O, Ogul H, Onel Y, Penzo A, Snyder C, Tiras E, Blumenfeld B, Corcodilos L, Davis J, Gritsan AV, Kang L, Kyriacou S, Maksimovic P, Roguljic M, Roskes J, Sekhar S, Swartz M, Vámi TÁ, Abreu A, Alcerro Alcerro LF, Anguiano J, Baringer P, Bean A, Flowers Z, Grove D, King J, Krintiras G, Lazarovits M, Le Mahieu C, Lindsey C, Marquez J, Minafra N, Murray M, Nickel M, Pitt M, Popescu S, Rogan C, Royon C, Salvatico R, Sanders S, Smith C, Wang Q, Wilson G, Allmond B, Ivanov A, Kaadze K, Kalogeropoulos A, Kim D, Maravin Y, Nam K, Natoli J, Roy D, Sorrentino G, Rebassoo F, Wright D, Adams E, Baden A, Baron O, Belloni A, Bethani A, Chen YM, Eno SC, Hadley NJ, Jabeen S, Kellogg RG, Koeth T, Lai Y, Lascio S, Mignerey AC, Nabili S, Palmer C, Papageorgakis C, Paranjpe MM, Wang L, Wong K, Bendavid J, Busza W, Cali IA, Chen Y, D'Alfonso M, Eysermans J, Freer C, Gomez-Ceballos G, Goncharov M, Harris P, Hoang D, Kovalskyi D, Krupa J, Lavezzo L, Lee YJ, Long K, Mironov C, Paus C, Rankin D, Roland C, Roland G, Rothman S, Shi Z, Stephans GSF, Wang J, Wang Z, Wyslouch B, Yang TJ, Crossman B, Joshi BM, Kapsiak C, Krohn M, Mahon D, Mans J, Marzocchi B, Pandey S, Revering M, Rusack R, Saradhy R, Schroeder N, Strobbe N, Wadud MA, Cremaldi LM, Bloom K, Bryson M, Claes DR, Fangmeier C, Golf F, Hossain J, Joo C, Kravchenko I, Reed I, Siado JE, Snow GR, Tabb W, Wightman A, Yan F, Yu D, Zecchinelli AG, Agarwal G, Bandyopadhyay H, Hay L, Iashvili I, Kharchilava A, McLean C, Morris M, Nguyen D, Pekkanen J, Rappoccio S, Rejeb Sfar H, Williams A, Alverson G, Barberis E, Haddad Y, Han Y, Krishna A, Li J, Lu M, Madigan G, Morse DM, Nguyen V, Orimoto T, Parker A, Skinnari L, Tishelman-Charny A, Wang B, Wood D, Bhattacharya S, Bueghly J, Chen Z, Hahn KA, Liu Y, Miao Y, Monk DG, Schmitt MH, Taliercio A, Velasco M, Band R, Bucci R, Castells S, Cremonesi M, Das A, Goldouzian R, Hildreth M, Ho KW, Hurtado Anampa K, Jessop C, Lannon K, Lawrence J, Loukas N, Lutton L, Mariano J, Marinelli N, Mcalister I, McCauley T, Mcgrady C, Mohrman K, Moore C, Musienko Y, Nelson H, Osherson M, Ruchti R, Townsend A, Wayne M, Yockey H, Zarucki M, Zygala L, Basnet A, Bylsma B, Carrigan M, Durkin LS, Hill C, Joyce M, Lesauvage A, Nunez Ornelas M, Wei K, Winer BL, Yates BR, Addesa FM, Bouchamaoui H, Das P, Dezoort G, Elmer P, Frankenthal A, Greenberg B, Haubrich N, Higginbotham S, Kopp G, Kwan S, Lange D, Loeliger A, Marlow D, Ojalvo I, Olsen J, Stickland D, Tully C, Malik S, Bakshi AS, Barnes VE, Chandra S, Chawla R, Das S, Gu A, Gutay L, Jones M, Jung AW, Kondratyev D, Koshy AM, Liu M, Negro G, Neumeister N, Paspalaki G, Piperov S, Purohit A, Schulte JF, Stojanovic M, Thieman J, Virdi AK, Wang F, Xie W, Dolen J, Parashar N, Pathak A, Acosta D, Baty A, Carnahan T, Dildick S, Ecklund KM, Fernández Manteca PJ, Freed S, Gardner P, Geurts FJM, Kumar A, Li W, Miguel Colin O, Padley BP, Redjimi R, Rotter J, Yigitbasi E, Zhang Y, Bodek A, de Barbaro P, Demina R, Dulemba JL, Fallon C, Garcia-Bellido A, Hindrichs O, Khukhunaishvili A, Parygin P, Popova E, Taus R, Van Onsem GP, Goulianos K, Chiarito B, Chou JP, Gershtein Y, Halkiadakis E, Hart A, Heindl M, Jaroslawski D, Karacheban O, Laflotte I, Lath A, Montalvo R, Nash K, Routray H, Salur S, Schnetzer S, Somalwar S, Stone R, Thayil SA, Thomas S, Vora J, Wang H, Acharya H, Ally D, Delannoy AG, Fiorendi S, Holmes T, Karunarathna N, Lee L, Nibigira E, Spanier S, Aebi D, Ahmad M, Bouhali O, Dalchenko M, Eusebi R, Gilmore J, Huang T, Kamon T, Kim H, Luo S, Malhotra S, Mueller R, Overton D, Rathjens D, Safonov A, Akchurin N, Damgov J, Hegde V, Hussain A, Kazhykarim Y, Lamichhane K, Lee SW, Mankel A, Mengke T, Muthumuni S, Peltola T, Volobouev I, Whitbeck A, Appelt E, Greene S, Gurrola A, Johns W, Kunnawalkam Elayavalli R, Melo A, Romeo F, Sheldon P, Tuo S, Velkovska J, Viinikainen J, Cardwell B, Cox B, Hakala J, Hirosky R, Ledovskoy A, Li A, Neu C, Perez Lara CE, Karchin PE, Aravind A, Banerjee S, Black K, Bose T, Dasu S, De Bruyn I, Everaerts P, Galloni C, He H, Herndon M, Herve A, Koraka CK, Lanaro A, Loveless R, Madhusudanan Sreekala J, Mallampalli A, Mohammadi A, Mondal S, Parida G, Pinna D, Savin A, Shang V, Sharma V, Smith WH, Teague D, Tsoi HF, Vetens W, Warden A, Afanasiev S, Andreev V, Andreev Y, Aushev T, Azarkin M, Babaev A, Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Chekhovsky V, Chistov R, Danilov M, Dermenev A, Dimova T, Druzhkin D, Dubinin M, Dudko L, Ershov A, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Gribushin A, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Korotkikh V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oreshkin V, Oskin A, Palichik V, Perelygin V, Petrov N, Petrushanko S, Polikarpov S, Popov V, Radchenko O, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Snigirev A, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. New Structures in the J/ψJ/ψ Mass Spectrum in Proton-Proton Collisions at sqrt[s]=13 TeV. PHYSICAL REVIEW LETTERS 2024; 132:111901. [PMID: 38563916 DOI: 10.1103/physrevlett.132.111901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 12/07/2023] [Accepted: 01/31/2024] [Indexed: 04/04/2024]
Abstract
A search is reported for near-threshold structures in the J/ψJ/ψ invariant mass spectrum produced in proton-proton collisions at sqrt[s]=13 TeV from data collected by the CMS experiment, corresponding to an integrated luminosity of 135 fb^{-1}. Three structures are found, and a model with quantum interference among these structures provides a good description of the data. A new structure is observed with a local significance above 5 standard deviations at a mass of 6638_{-38}^{+43}(stat)_{-31}^{+16}(syst) MeV. Another structure with even higher significance is found at a mass of 6847_{-28}^{+44}(stat)_{-20}^{+48}(syst) MeV, which is consistent with the X(6900) resonance reported by the LHCb experiment and confirmed by the ATLAS experiment. Evidence for another new structure, with a local significance of 4.7 standard deviations, is found at a mass of 7134_{-25}^{+48}(stat)_{-15}^{+41}(syst) MeV. Results are also reported for a model without interference, which does not fit the data as well and shows mass shifts up to 150 MeV relative to the model with interference.
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Chen Z, Xiao G, Ao J. Resveratrol Attenuates Rheumatoid Arthritis Induce Neutrophil Extracellular Traps via TLR-4 Mediated Inflammation in C57BL/6 Mice. Physiol Res 2024; 73:91-104. [PMID: 38466008 PMCID: PMC11019621 DOI: 10.33549/physiolres.935172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/17/2023] [Indexed: 04/26/2024] Open
Abstract
The objective of this study was to evaluate whether RSV inhibits neutrophil extracellular traps (NETs) that induce joint hyperalgesia in C57BL/6 mice after adjuvant-induced arthritis. A subplantar injection of Freund's complete adjuvant was administered to C57BL/6 mice on day 0 for immunization in the AIA model. Resveratrol (RSV, 25 mg/kg) was administered intraperitoneally once daily starting on day 22 and continuing for two weeks. The effects of mechanical hyperalgesia and edema formation have been assessed in addition to histopathological scoring. Mice were sacrificed on day 35 to determine cytokine levels and PADI4 and COX-2 expression levels. ELISA was used to quantify neutrophil extracellular traps (NETs) along with neutrophil elastase-DNA and myeloperoxidase-DNA complexes in neutrophils. An immunohistochemical stain was performed on knee joints to determine the presence of nuclear factor kappa B p65 (NF-kappaB p65). AIA mice were found to have higher levels of NET in joints and their joint cells demonstrated an increased expression of the PADI4 gene. Treatment with RSV in AIA mice (25 mg/kg, i.p.) significantly (P<0.05) inhibited joint hyperalgesia, resulting in a significant increase in mechanical threshold, a decrease in articular edema, a decrease in the production of inflammatory cytokines, increased COX-2 expression, and a decrease in the immunostaining of NF-kappaB. Furthermore, treatment with RSV significantly reduced the amount of neutrophil elastase (NE)-DNA and MPO-DNA complexes, which were used as indicators of NET formation (P<0.05). This study indicates that RSV reduces NET production and hyperalgesia by reducing inflammation mediated by PADI4 and COX-2. According to these data, NETs contribute to joint pain and resveratrol can be used to treat pain in RA through this pathway.
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Huang Z, Chen Z, Song E, Yu P, Chen W, Lin H. Bioinformatics Analysis and Experimental Validation for Exploring Key Molecular Markers for Glioblastoma. Appl Biochem Biotechnol 2024:10.1007/s12010-024-04894-7. [PMID: 38446410 DOI: 10.1007/s12010-024-04894-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2024] [Indexed: 03/07/2024]
Abstract
Glioblastoma (GBM) is the most common primary intracranial malignancy with a very low survival rate. Exploring key molecular markers for GBM can help with early diagnosis, prognostic prediction, and recurrence monitoring. This study aims to explore novel biomarkers for GBM via bioinformatics analysis and experimental verification. Dataset GSE103229 was obtained from the GEO database to search differentially expressed lncRNA (DELs), mRNAs (DEMs), and miRNAs (DEMis). Hub genes were selected to establish competing endogenous RNA (ceRNA) networks. The GEPIA database was employed for the survival analysis and expression detection of hub genes. Hub gene expression in GBM tissue samples and cell lines was validated using RT-qPCR. Western blotting was employed for protein expression evaluation. SYT1 overexpression vector was transfected in GBM cells. CCK-8 assay and flow cytometry were performed to detect the malignant phenotypes of GBM cells. There were 901 upregulated and 1086 downregulated DEMs identified, which were prominently enriched in various malignancy-related functions and pathways. Twenty-two hub genes were selected from PPI networks. Survival analysis and experimental validation revealed that four hub genes were tightly associated with GBM prognosis and progression, including SYT1, GRIN2A, KCNA1, and SYNPR. The four genes were significantly downregulated in GBM tissues and cell lines. Overexpressing SYT1 alleviated the proliferation and promoted the apoptosis of GBM cells in vitro. We identify four genes that may be potential molecular markers of GBM, which may provide new ideas for improving early diagnosis and prediction of the disease.
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Hilario A, Salvador E, Cardenas A, Romero J, Lechuga C, Chen Z, Martinez de Aragon A, Perez-Nuñez A, Hernandez-Lain A, Sepulveda J, Lagares A, Toldos O, Rodriguez-Gonzalez V, Ramos A. Low rCBV values in glioblastoma tumor progression under chemoradiotherapy. Neuroradiology 2024; 66:317-323. [PMID: 38183424 DOI: 10.1007/s00234-023-03279-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/26/2023] [Indexed: 01/08/2024]
Abstract
PURPOSE After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence. METHODS Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software. RESULTS Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time. CONCLUSION Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.
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Zhang C, Chen Z. [Advances in the technology of surgical treatment for atlantoaxial dislocation]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:182-186. [PMID: 38291633 DOI: 10.3760/cma.j.cn112139-20231219-00287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The etiology and pathological morphology of atlantoaxial dislocation (AAD) are complex. Based on the pathological anatomical characteristics of AAD, combined with clinical techniques, it is essential to formulate reasonable classification criteria and develop corresponding treatment strategies for different types of AAD. The satisfactory outcome of surgical treatment for AAD can only be achieved through the comprehensive application of various atlantoaxial reduction techniques, tension band releasing techniques, internal fixation and fusion techniques. This article discusses the latest advancements in surgical treatment techniques for AAD, thoroughly explores treatment strategies based on different types of AAD, and analyzes the practicality and effectiveness of clinical classification and treatment strategies. The posterior atlantoaxial facet releasing and distraction compression reduction technique may pose challenges to traditional treatment strategies in the future. In the development of surgical treatment techniques for AAD, microspinal surgical techniques may play a significant role in improving surgical methods and enhancing treatment outcomes.
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Wang JL, Zhang BY, Qi MY, Meng HF, Jin TY, Chen Z, Duan WR. [Clinical evaluation methods for craniovertebral junction abnormalities]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:260-264. [PMID: 38291643 DOI: 10.3760/cma.j.cn112139-20230717-00013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Craniovertebral junction malformation is a congenital malformation located in the foramen magnum and upper cervical spine, including bone and nerve malformation, resulting in motor and sensory disorders, cerebellar and lower cranial nerves, etc. The evaluation methods of clinical symptoms and efficacy of craniovertebral junction malformation are important for the surgical indications and effects, mainly including the evaluation of clinical symptoms and the quality of life. At present, the commonly used methods in clinical work and literature are the Japanese orthopaedic association scores, visual analogue scales, 36-item short-form health survey, etc. Most of these clinical evaluations are not aimed at craniovertebral junction diseases but focus on the description of a certain type of clinical symptoms. Chicago Chiari outcome scale and syringomyelia outcome scale of Xuanwu hospital are dedicated to Craniovertebral junction malformation, but more clinical studies are needed to prove their effectiveness. Based on the literature reports, this article reviewed the previous clinical evaluation methods of craniovertebral junction malformation and discusses their applications and limitations.
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Wang H, Shi L, Xiong Z, Ma S, Cao H, Cai S, Qiao Z, Pan J, Chen Z. A two-dimensional metal-organic framework assembled from scandium-based cages for the selective capture of sulfur hexafluoride. Chem Commun (Camb) 2024; 60:2397-2400. [PMID: 38323363 DOI: 10.1039/d3cc05087d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Herein, we report the synthesis of a two-dimensional metal-organic framework (MOF), assembled from octahedral metal-organic cages featuring phenanthroline-based carboxylate linkers and μ3-oxo-centered trinuclear Sc(III) inorganic building blocks. We study the performance of this MOF towards the capture of sulfur hexafluoride (SF6). On account of its structural features and porous nature, this MOF displays an SF6 uptake capacity of 0.92 mmol g-1 at 0.1 bar and an isosteric heat of adsorption of about 30.7 kJ mol-1 for SF6, illustrating its potential application for the selective capture of SF6 from N2. In addition, we study the adsorptive binding mechanism of SF6 and N2 inside this MOF via molecular simulations.
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Zahmatkesh S, Chen Z, Khan NA, Ni BJ. Removing polyfluoroalkyl substances (PFAS) from wastewater with mixed matrix membranes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168881. [PMID: 38042200 DOI: 10.1016/j.scitotenv.2023.168881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 12/04/2023]
Abstract
Polyfluoroalkyl and perfluoroalkyl (PFAS) chemicals are fluorinated and exhibit complicated behavior. They are determined and highly resistant to ecological modifications that render plants ecologically robust. Thermal stability and water and oil resistance are examples of material qualities. Their adverse consequences are causing increasing worry due to their bioaccumulative nature in humans and other creatures. Direct data indicates that PFAS exposure in humans causes endocrine system disruption, immune system suppression, obesity, increased cholesterol, and cancer. Several PFASs are present in drinking water at low doses and may harm people. These cancer-causing PFAS have caused concern for water bodies all around the globe. Analytical techniques are used to identify and measure PFAS in an aqueous medium (membrane). Furthermore, a deeper explanation is provided for PFAS removal methods, including mixed matrix membrane (MMM) technology. By removing over 99 % of the PFAS from wastewater, MMMs may effectively remove PFAS from sewage when the support matrix contains adsorbing components. Furthermore, we consider several factors affecting the removal of PFAS and practical sorption methods for PFAS onto various adsorbents.
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